Interaction kinetics with transcriptomic and secretory responses of CD19-CAR natural killer-cell therapy in CD20 resistant non-hodgkin lymphoma
LEUKEMIA
Authors: Ravi, Dashnamoorthy; Sarkar, Saheli; Purvey, Sneha; Passero, Frank; Beheshti, Afshin; Chen, Ying; Mokhtar, Maisarah; David, Kevin; Konry, Tania; Evens, Andrew M.
Abstract
We investigated the cytolytic and mechanistic activity of anti-CD19 chimeric antigen receptor natural killer (CD19.CAR.NK92) therapy in lymphoma cell lines (diffuse large B-cell, follicular, and Burkitt lymphoma), including rituximab- and obinutuzumab-resistant cells, patient-derived cells, and a human xenograft model. CD19.CAR.NK92 therapy significantly increased cytolytic activity at E:T ratios (1:1-10:1) via LDH release and prominent induction of apoptosis in all cell lines, including in anti-CD20 resistant lymphoma cells. The kinetics of CD19.CAR.NK92 cell death measured via droplet-based single cell microfluidics analysis showed that most lymphoma cells were killed by single contact, with anti-CD20 resistant cell lines requiring significantly longer contact duration with NK cells. In addition, systems biology transcriptomic analyses of flow-sorted lymphoma cells co-cultured with CD19.CAR.NK92 revealed conserved activation of IFN gamma signaling, execution of apoptosis, ligand binding, and immunoregulatory and chemokine signaling pathways. Furthermore, a 92-plex cytokine panel analysis showed increased secretion of granzymes, increased secretion of FASL, CCL3, and IL10 in anti-CD20 resistant SUDHL4 cells with induction of genes relevant to mTOR and G2/M checkpoint activation, which were noted in all anti-CD20 resistant cells co-cultured with CD19.CAR.NK92 cells. Collectively, CD19.CAR.NK92 was associated with potent anti-lymphoma activity across a host of sensitive and resistant lymphoma cells that involved distinct immuno-biologic mechanisms of cell death.
A Quantitative Systems Pharmacology Model for the Key Interleukins Involved in Crohn's Disease
JOURNAL OF PHARMACOLOGY AND EXPERIMENTAL THERAPEUTICS
Authors: Balbas-Martinez, Violeta; Asin-Prieto, Eduardo; Parra-Guillen, Zinnia P.; Troconiz, Inaki F.
Abstract
Crohn's disease (CD) is a complex inflammatory bowel disease whose pathogenesis appears to involve several immunologic defects causing functional impairment of the gut. Its complexity and the reported loss of effectiveness over time of standard of care together with the increase in its worldwide incidence require the application of techniques aiming to find new therapeutic strategies. Currently, systems pharmacology modeling has been gaining importance as it integrates the available knowledge of the system into a single computational model. In this work, the following workflow for robust application of systems pharmacology modeling was followed: 1) scope definition; 2) species selection and circulating plasma levels based on a search in the literature; 3) representation of model topology and parametrization of the interactions, after literature data extraction and curation, and the implementation of ordinary differential equations in SimBiology (MATLAB version R2018b); and 4) model curation and evaluation by visual comparison of simulated interleukin (IL) concentrations with the reported levels in plasma, and sensitivity analysis performed to confirm model robustness and identify the most influential parameters. Finally, 5) exposure to two dose levels of recombinant human IL10 was evaluated by simulation and comparison with reported clinical study results. In summary, we present a quantitative systems pharmacology model for the main ILs involved in CD developed using a standardized methodology and supported by a comprehensive repository summarizing the most relevant literature in the field. However, it has to be taken into account that external validation is still pending as available clinical data were primarily used for model training. SIGNIFICANCE STATEMENT Crohn's disease (CD) is a complex heterogeneous inflammatory bowel disorder. Systems pharmacology modeling offers a great opportunity for integration of the available knowledge on the disease using a computational framework. As a result of this work, a comprehensive repository along with a quantitative systems pharmacology model for the main interleukins involved in CD is provided. This model is useful for the in silico evaluation of biomarkers and potential therapeutic targets and can be adapted to address research gaps regarding CD.